Energy-aware flexible job shop scheduling under time-of-use pricing

Abstract

Compromising productivity in exchange for energy-saving does not appeal to capital-intensive manufacturing industries. However, we might be able to maintain the same productivity while significantly reducing the energy-cost. This paper addresses a flexible job shop scheduling under time-of-use pricing and scheduled downtime aiming to minimize makespan and total energy cost. First, an integer linear programming model is proposed. Second, a constraint programming model is proposed. Third, a managerial insight is derived. The computational study demonstrates we can maintain the maximum productivity while significantly reducing the energy-cost by 6.9% on average in large-sized benchmark instances.